Exploring the risks and benefits of flexibility in biodiversity offset location in a case study of migratory shorebirds

Biodiversity offsets aim to counterbalance the residual impacts of development on species and ecosystems. Guidance documents explicitly recommend that biodiversity offset actions be located close to the location of impact because of higher potential for similar ecological conditions, but allowing greater spatial flexibility has been proposed. We examined the circumstances under which offsets distant from the impact location could be more likely to achieve no net loss or provide better ecological outcomes than offsets close to the impact area. We applied a graphical model for migratory shorebirds in the East Asian–Australasian Flyway as a case study to explore the problems that arise when incorporating spatial flexibility into offset planning. Spatially flexible offsets may alleviate impacts more effectively than local offsets; however, the risks involved can be substantial. For our case study, there were inadequate data to make robust conclusions about the effectiveness and equivalence of distant habitat-based offsets for migratory shorebirds. Decisions around offset placement should be driven by the potential to achieve equivalent ecological outcomes; however, when considering more distant offsets, there is a need to evaluate the likely increased risks alongside the potential benefits. Although spatially flexible offsets have the potential to provide more cost-effective biodiversity outcomes and more cobenefits, our case study showed the difficulty of demonstrating these benefits in practice and the potential risks that need to be considered to ensure effective offset placement.     

Social justice and mobility in coastal Louisiana,USA

Regional Environmental Change - Louisiana faces extensive coastal land loss which threatens the livelihoods of marginalized populations. These groups have endured extreme disruptive events in the...     

Probability analyses of combining background concentrations with model-predicted concentrations

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.

Implications: EPA's current approaches to determining background concentrations for compliance modeling purposes often lead to “double counting” of background concentrations and actual plume impacts and thus lead to overpredictions of total impacts. Further, the current Tier 1 approach of simply adding the top ends of the background and model predicted concentrations (e.g., adding the 99th percentiles of these distributions together) results in design value concentrations at probabilities in excess of the form of the National Ambient Air Quality Standards.     

The role of digital data entry in participatory environmental monitoring

Many argue that monitoring conducted exclusively by scientists is insufficient to address ongoing environmental challenges. One solution entails the use of mobile digital devices in participatory monitoring (PM) programs. But how digital data entry affects programs with varying levels of stakeholder participation, from nonscientists collecting field data to nonscientists administering every step of a monitoring program, remains unclear. We reviewed the successes, in terms of management interventions and sustainability, of 107 monitoring programs described in the literature (hereafter programs) and compared these with case studies from our PM experiences in Australia, Canada, Ethiopia, Ghana, Greenland, and Vietnam (hereafter cases). Our literature review showed that participatory programs were less likely to use digital devices, and 2 of our 3 more participatory cases were also slow to adopt digital data entry. Programs that were participatory and used digital devices were more likely to report management actions, which was consistent with cases in Ethiopia, Greenland, and Australia. Programs engaging volunteers were more frequently reported as ongoing, but those involving digital data entry were less often sustained when data collectors were volunteers. For the Vietnamese and Canadian cases, sustainability was undermined by a mismatch in stakeholder objectives. In the Ghanaian case, complex field protocols diminished monitoring sustainability. Innovative technologies attract interest, but the foundation of effective participatory adaptive monitoring depends more on collaboratively defined questions, objectives, conceptual models, and monitoring approaches. When this foundation is built through effective partnerships, digital data entry can enable the collection of more data of higher quality. Without this foundation, or when implemented ineffectively or unnecessarily, digital data entry can be an additional expense that distracts from core monitoring objectives and undermines project sustainability. The appropriate role of digital data entry in PM likely depends more on the context in which it is used and less on the technology itself.     

Integrated spatial health assessment of yellow perch (<Emphasis Type="Italic">Perca flavescens</Emphasis>) populations from the St. Lawrence River,Quebec, Canada) part A: physiological parameters and pathogen assessment

A multi-disciplinary approach was used to evaluate the health of yellow perch (Perca flavescens) in the St. Lawrence River (Quebec, Canada), which is experiencing a severe population decline in the downstream portion of the river. Physiological parameters, liver alterations, trace metal concentrations, parasite prevalence and abundance, stable isotope composition, and the presence/absence of the viral hemorragic septicemia virus (VHSV) were evaluated in perch collected at six sites along the river: Lake St. François, Lake St. Louis (north and south), Beauregard Island, and Lake St. Pierre (north and south). Trace metal concentrations in surface water were higher in Lake St. Louis and downstream of a major urban wastewater treatment plant discharge, indicating that this effluent was a significant source of Cu, As, Ag, Zn, and Cd. Levels of Pb in surface water exceeded thresholds for the protection of aquatic life in Lake St. Louis and were negatively correlated with body condition index in this lake. In Lake St. Pierre, Cu, Ag, and Cd bioaccumulated significantly in perch liver and lower body condition index and greater liver damage were observed compared to upstream sites. Parasite analyses indicated a higher abundance of metacercariae of the trematodes Apophallus brevis and Diplostomum spp. in Lake St. Louis, and VHSV was not detected in the liver of yellow perch for all studied sites. Overall, results suggested that the global health of yellow perch from Lake St. Pierre is lower compared to upstream studied sites, which could contribute to the documented population collapse at this site.     

Integrated spatial health assessment of yellow perch (Perca flavescens) populations from the St. Lawrence River (QC,Canada), part B: cellular and transcriptomic effects

Environmental Science and Pollution Research - Multi-biological level assessments have become great tools to evaluate the health of aquatic ecosystems. Using this approach, a complementary study...